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On the modern battlefield, fighting capabilities, such as speed, target detection range, target identification capabilities, and shooting effectiveness, of short-range artillery rocket sets (ARSs) are constantly being improved. Problems arise when attempting to successfully fire such kits in the face of disruption from both the cannon and the moving platform on which the cannon is mounted. Furthermore, the set is a variable mass system since it can fire anywhere from a few to dozens or even hundreds of missiles in a brief period of time, implying that the ARS is a highly nonlinear system of variable parameters (non-stationary). This work shows how to control such a system. If the ARS is placed on a moving basis where there is both a system and measurement noise, the state variables must be restored, and the ARS data must be filtered. Therefore, in addition to the LQR regulator, an extended Kalman filter was used. As a consequence of this synthesis, an LQG (linear quadratic Gaussian) regulator of ARS was obtained, which was used to follow the target along the line of sight. The key goal of this paper is to develop control algorithms that will increase the performance of ARS control in elevation and azimuth, as well as the accuracy of achieving and eliminating maneuverable air targets. Moreover, through the quality criterion adopted, we hope to affect control energy costs while maintaining control precision. Graphical representations of certain computational simulation results are provided.

The Remote Control of the Artillery Rocket Set as a Strongly Nonlinear System Subject to Random Loads